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📉 '''Exceedance probability''' is a statistical measure used in insurance and [[Definition:Catastrophe modeling | catastrophe modeling]] to express the likelihood that a given level of [[Definition:Loss | loss]] will be exceeded within a specified time period, most commonly one year. If a [[Definition:Catastrophe model | catastrophe model]] reports that a $500 million loss has a 2% annual exceedance probability, it means there is a 2-in-100 chance in any given year that losses from a modeled peril — such as hurricane, earthquake, or flood — will surpass that threshold. The concept is central to how [[Definition:Insurance carrier | insurers]], [[Definition:Reinsurance | reinsurers]], and [[Definition:Rating agency | rating agencies]] quantify and communicate tail risk in property catastrophe portfolios.

📊 Analysts derive exceedance probabilities from stochastic event sets generated by [[Definition:Catastrophe model | catastrophe models]]. These models simulate tens of thousands of possible disaster scenarios, assign each a frequency of occurrence, and calculate the resulting insured losses to a portfolio. The output is typically organized into an [[Definition:Exceedance probability curve | exceedance probability curve]], which plots the full spectrum of loss levels against their associated probabilities. Two flavors are standard: the occurrence exceedance probability (OEP), which considers the single largest event in a year, and the aggregate exceedance probability (AEP), which sums all event losses within a year. Each serves different decision-making needs — OEP is commonly used for structuring [[Definition:Per-occurrence reinsurance | per-occurrence reinsurance]], while AEP informs [[Definition:Aggregate reinsurance | aggregate covers]] and overall capital planning.

💡 Getting exceedance probability right has direct financial consequences. [[Definition:Reinsurance | Reinsurers]] price [[Definition:Catastrophe excess-of-loss reinsurance | catastrophe excess-of-loss layers]] based on modeled exceedance probabilities at various return periods, and [[Definition:Rating agency | rating agencies]] such as AM Best and S&P use these metrics to evaluate whether an insurer holds sufficient [[Definition:Risk-based capital (RBC) | capital]] relative to its catastrophe exposure. Regulators in states like Florida also reference exceedance probability outputs when stress-testing insurer solvency. Because small shifts in modeled probability can translate into large differences in required capital or [[Definition:Reinsurance premium | reinsurance pricing]], the assumptions underlying the models — event frequency, vulnerability functions, exposure data quality — receive intense scrutiny from all stakeholders.

'''Related concepts:'''
{{Div col|colwidth=20em}}
* [[Definition:Exceedance probability curve]]
* [[Definition:Catastrophe model]]
* [[Definition:Probable maximum loss (PML)]]
* [[Definition:Return period]]
* [[Definition:Aggregate exceedance probability (AEP)]]
* [[Definition:Occurrence exceedance probability (OEP)]]
{{Div col end}}

Definition:Exceedance probability - Revision history

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